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Likelier
Other · reviewed 2026-05-09

What is the probability of a civilian being killed or seriously injured during a Ukraine-scale conventional conflict over five years?

Evidence quality 4.75/5

Eight-dimension review score against the quality rubric . Each dimension scored 1–5.

D1 Source grounding
5/5
D2 Source authority
5/5
D3 Arithmetic
5/5
D4 Uncertainty
4/5
D5 Scope
5/5
D6 Prose
5/5
D7 Perception honesty
4/5
D8 Caveat completeness
5/5
Average 4.75/5
Direct evidence

Lifetime probability · lifetime, subgroup

1 in 499

0.2% lifetime chance

Most people underestimate this.

range 1 in 833 to 1 in 200

lifetime, subgroup each band = 10× rarer → zoomed to your factors See full scale →
certain 1 in 1K 1 in 1M 1 in 1B
1 in 50 1 in 4,990

● your factors — click this risk ▾ to reveal

≈ As likely as

An empty residential street with a damaged building in the background, flat vector illustration in muted grey and olive tones.

Perceived

People in countries not currently experiencing war typically have poorly calibrated intuitions about civilian casualty rates in conventional conflicts. Media coverage of major attacks and dramatic imagery from Ukraine drives availability-heuristic overestimates for those far from the war, while proximity and familiarity with specific incidents can cause underestimation in affected populations who normalize gradual attrition. No high-quality survey specifically asks populations to estimate the per-civilian probability of being killed or injured in a Ukraine-type conflict, so the perceived side is editorial intuition. Rough public estimates tend to cluster vaguely around "very dangerous" without distinguishing proximity to the front, city versus rural, or duration of exposure.

Rough estimate: ~1 in 50 feels plausible to many Western observers; actual verified rate is closer to 1 in 500 over five years

Source: editorial intuition, not polled

Actual

51,924 civilians (14,383 killed + 37,541 injured) confirmed by OHCHR through October 2025, against ~37 million residents remaining in Ukrainian-controlled territory

Civilians residing in Ukrainian-controlled territory during the full-scale invasion, excluding the approximately 6-7 million who fled abroad

Show derivation

The UN Human Rights Monitoring Mission in Ukraine (HRMMU/OHCHR) confirmed 14,383 civilians killed and 37,541 injured from February 24, 2022 through October 2025, a period of approximately 3.5 years. The HRMMU explicitly acknowledges that "the real number is higher" due to verification lag and restricted access in Russian-occupied territories. Native numerator: 51,924 (killed + injured). Native denominator: approximately 37 million residents who remained in Ukrainian-controlled territory, derived by subtracting approximately 6-7 million refugees who left the country from a pre-war Kyiv-controlled population of roughly 44 million (UN/UNHCR refugee figures, noting ~4.5 million returns partially offset the outflow). The 3.5-year rate of 51,924 / 37,000,000 = 0.001403. Linearly extrapolated to 5 years: 51,924 × (5/3.5) / 37,000,000 = 74,177 / 37,000,000 = 0.002004. The linear extrapolation is conservative because 2025 showed a 31% increase in casualties over 2024 (HRMMU 2025 annual report), suggesting the rate has been accelerating rather than staying flat. The normalized scope is subgroup_lifetime because this is a conflict-period probability specific to the civilian-in-war subgroup rather than a general US adult lifetime risk. Killed-only 5-year rate: 14,383 × (5/3.5) / 37,000,000 = 0.000556 (~1 in 1,800 for death alone).

Caveats: The OHCHR figures are confirmed minimum counts. The monitoring mission operates …

The OHCHR figures are confirmed minimum counts. The monitoring mission operates under access restrictions in Russian-occupied territories and acknowledges verification lag for casualties in contested areas. Independent analysts have estimated true civilian casualty totals at 1.5-3 times the verified count, which would push the 5-year rate toward the upper end of the uncertainty range. The denominator of approximately 37 million residents is itself uncertain; Ukraine has not conducted a census since 2001, and the statistical service paused demographic reporting during the war. Internal displacement (people who stayed in Ukraine but moved away from front-line regions) further complicates attribution. Casualty risk is highly heterogeneous by geography: residents of Donetsk, Kharkiv, Zaporizhzhia, and Kherson oblasts face risk several times the national average, while western Ukraine experiences comparatively low per-capita casualty rates despite missile strikes on energy infrastructure.

Regional breakdown

The headline figure averages across very different populations. Here’s how the probability varies by geography or context:

Region / context Lifetime probability Notes
Civilians across Ukrainian-controlled territory (all zones, 2022-2025) 1 in 499 Headline figure. 51,924 OHCHR-confirmed casualties / 37M resident population, linearly extrapolated from 3.5 to 5 years.
Civilians killed only (not injured) — 5-year extrapolation 1 in 1,799 14,383 killed / 37M × (5/3.5). Death-only rate is approximately 1 in 1,800 over a 5-year conflict.
Civilians in active front-line oblasts (Donetsk, Kharkiv, Zaporizhzhia) 1 in 67 Order-of-magnitude estimate only. OHCHR data shows Donetsk and Luhansk regions accounted for approximately 54% of verified casualties despite holding a smaller share of the population. Residents of active-combat oblasts face risk several times higher than the national average.
Civilians in rear areas (Lviv, western Ukraine) 1 in 5,000 Order-of-magnitude estimate only. Western oblasts have experienced missile and drone strikes but far fewer casualties per capita than eastern and southern zones.

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Frontline soldier casualty

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War (civilian)

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Landmine or UXO injury

What are the odds of being killed or injured by a landmine or unexploded ordnance?

Compare to:

The UN Human Rights Monitoring Mission in Ukraine (HRMMU) has confirmed at least 14,383 civilians killed and 37,541 injured from February 2022 through October 2025 — roughly 3.5 years of full-scale conflict. Against a resident population of approximately 37 million people who remained in Ukrainian-controlled territory (after subtracting the 6-7 million who fled abroad as refugees), this yields a confirmed cumulative casualty rate of about 1 in 713 over 3.5 years. Linearly extrapolated to a five-year conflict, the combined killed-and-seriously-injured rate reaches approximately 1 in 500, or 0.2% of the civilian population. The killed-only rate over five years is closer to 1 in 1,800 (0.056%). These are confirmed, verified figures; the HRMMU explicitly states that the real totals are higher because verification in Russian-occupied territories is incomplete.

The perception gap runs in both directions. Western observers exposed primarily to dramatic footage and milestone casualty counts tend to overestimate the per-civilian probability, imagining something closer to 1 in 50 or 1 in 20. Residents of Ukraine who have not personally experienced nearby strikes may underestimate the aggregate rate by anchoring to their local experience. Both errors stem from the same mechanism: civilians are most salient as statistics when an incident is large enough to make the news, which produces a biased sample of the underlying distribution. The true distribution includes thousands of smaller incidents — individual shelling deaths, single drone strikes, one-off missile impacts — that collectively account for much of the total but receive little international attention.

The national average conceals enormous geographic heterogeneity. OHCHR data for early 2022 showed that Donetsk and Luhansk oblasts accounted for roughly 54% of verified casualties while holding a far smaller share of the country’s population. Residents within 20 kilometers of active front lines face casualty risks an order of magnitude above the national figure; residents of Lviv and other western oblasts face risks closer to those of a country not formally at war, despite periodic long-range missile strikes. The 1-in-500 headline figure is best understood as an average across a population with highly unequal exposure, not as a uniform individual probability.

Claim ledger

Every number below is what each source reported, with the verbatim quote we relied on and how we arrived at our figure. Click any link to verify directly.

  1. [1] UN Human Rights Monitoring Mission in Ukraine (HRMMU/OHCHR) — Ukraine's Civilians Face Daily Death and Injury Amid Intense Attacks, UN Human Rights Monitors Say
    Ukraine's Civilians Face Daily Death and Injury Amid Intense Attacks, UN Human Rights Monitors Say
    Statistic
    Since Russia launched its full-scale invasion of Ukraine in February 2022 through October 2025, HRMMU documented at least 14,383 civilians killed, including 738 children, and 37,541 injured, including 2,318 children.
    Excerpt
    “"Since Russia launched its full-scale invasion of Ukraine in February 2022, HRMMU has documented at least 14,383 civilians killed, including 738 children, and 37,541 injured, including 2,318 children." ”
    Source data from
    2025-10-01
    Accessed
    2026-05-09 · archived copy
    Calculation
    This is the primary numerator source. 14,383 killed + 37,541 injured = 51,924 total confirmed civilian casualties through approximately October 2025, covering 3.5 years of full-scale conflict. OHCHR explicitly states these are minimum confirmed figures and the real totals are higher. Used as the basis for native numerator and for the 3.5-year rate, which is then linearly extrapolated to 5 years.
    Independence
    HRMMU is the UN's own monitoring mission operating within Ukraine. It draws on field verification teams, court records, medical records, and on-site interviews. Its methodology is distinct from Ukrainian government figures and from media-based counts such as Airwaves or ACLED.
  2. [2] UN Human Rights Monitoring Mission in Ukraine (HRMMU/OHCHR) — 2025 deadliest year for civilians in Ukraine since 2022, UN human rights monitors find
    2025 deadliest year for civilians in Ukraine since 2022, UN human rights monitors find
    Statistic
    In 2025, conflict-related violence killed 2,514 civilians and injured 12,142 — 31% more killed and injured than in 2024 (2,088 killed; 9,138 injured).
    Excerpt
    “"The total number of killed and injured civilians in 2025 was 31 per cent higher than in 2024 (2,088 killed; 9,138 injured) and 70 per cent higher than in 2023 (1,974 killed; 6,651 injured)." ”
    Source data from
    2026-01-12
    Accessed
    2026-05-09 · archived copy
    Calculation
    Provides year-by-year trend data confirming the annual casualty progression: 2023 (1,974 killed; 6,651 injured), 2024 (2,088 killed; 9,138 injured), 2025 (2,514 killed; 12,142 injured). The escalating trend means linear 5-year extrapolation from the 3.5-year average likely understates the true 5-year total, supporting the upper end of the uncertainty range. Year 2022 figures (6,884 killed; 10,947 injured through December 26, 2022 per an earlier OHCHR update) show the invasion's first year was the deadliest, explaining the 3.5-year aggregate.
    Independence
    Same HRMMU mission but a later reporting period — provides cross-check consistency on annual figures. The year-by-year data is additive to and consistent with the cumulative total from the first source.
  3. [3] UNHCR (United Nations High Commissioner for Refugees) — Ukraine Refugee Situation — Operational Data Portal
    Ukraine Refugee Situation — Operational Data Portal
    Statistic
    As of September 2025, approximately 5.7 million Ukrainian refugees were recorded worldwide, with approximately 6.2 million recorded as of December 2024 — supporting the estimate of 6-7 million Ukrainians who left the country.
    Excerpt
    “"As of September 2025, the UNHCR has recorded 5.7 million Ukrainian refugees around the world, with 90% of this figure residing in various European countries outside of Ukraine." ”
    Source data from
    2025-09-01
    Accessed
    2026-05-09 · archived copy
    Calculation
    Provides the basis for the denominator adjustment from pre-war population (~44M Kyiv-controlled residents) to conflict-period resident population (~37M). The ~6-7M refugee outflow figure is derived from UNHCR's 5.7M registered figure plus unregistered displacees, minus approximately 4.5M returns (UNHCR December 2023 data showing 4.5 million returns to habitual residence). Net outflow used for denominator: approximately 7 million, giving a conflict-period resident population of ~37M.
    Independence
    Independent of HRMMU/OHCHR on data collection methodology and source.

412 risks with measured probability
1 in 10 1 in 100 1 in 1K 1 in 10K 1 in 100K 1 in 1M 1 in 10M 1 in 100M 1 in 1B certain rarer → Cosmetic surgery abroad risk — 1 in 10 Infant sugar/salt and adult disease — 1 in 10 Endometriosis — 1 in 10 Hair transplant Turkey risk — 1 in 10 Knee replacement — 1 in 10 Chronic painkillers — 1 in 10 Elderly abandonment — 1 in 9.1 Complete tooth loss — 1 in 9.1 Alzheimer's — 1 in 8.3 Sleep deprivation — 1 in 8.3 Smokeless tobacco — 1 in 8.3 Cycling w/o helmet — 1 in 8.0 Bruxism tooth damage — 1 in 7.7 Vision loss — 1 in 6.7 Hernia from lifting — 1 in 6.7 Hip fracture risk — 1 in 6.7 Regular drinking — 1 in 6.7 First heart attack — 1 in 5.9 Infertility — 1 in 5.7 5+ years paid LTC — 1 in 5.6 CTE (football) — 1 in 5.0 Major depression — 1 in 4.9 Hiking injury — 1 in 4.8 Infection from sharing food with child — 1 in 4.2 Lyme disease — 1 in 4.0 Loneliness & health — 1 in 3.8 Job loss & depression — 1 in 3.7 Inheriting AUD risk — 1 in 3.5 Alcohol use disorder — 1 in 3.4 Menopause CV risk acceleration — 1 in 3.0 Silent diabetes — 1 in 3.0 Flying with cold — 1 in 2.9 Tick illness (forest) — 1 in 2.9 Silent high cholesterol — 1 in 2.9 Grandparent loss in childhood — 1 in 2.8 Pacifier floor drop — 1 in 2.8 Drug-resistant infection — 1 in 2.6 No marrow match — 1 in 2.4 Nursing home admission — 1 in 2.2 Skipping dental checkups — 1 in 2.1 False-positive mammogram — 1 in 2.0 Regular smoking — 1 in 2.0 Travelers' diarrhea — 1 in 2.0 Adventure sports — 1 in 1.8 Family caregiver probability — 1 in 1.8 LTC need after 65 — 1 in 1.8 Widowhood probability — 1 in 1.7 Unprotected sex — 1 in 1.5 Silent hypertension — 1 in 1.3 Chronic back pain — 1 in 1.3 Hand hygiene — 1 in 1.0 Cancer (any) — 1 in 7.1 E-scooter no helmet — 1 in 4.5 E-bike no helmet — 1 in 4.0 Mishandled luggage — 1 in 3.7 Deer collision — 1 in 2.7 At-fault injury crash — 1 in 2.5 Flight cancellation — 1 in 1.8 Trip disruption: war or disaster — 1 in 1.7 Home burglary (global) — 1 in 9.1 Hitchhiking assault — 1 in 8.8 Mail check fraud — 1 in 7.7 Child sexual abuse — 1 in 6.8 Stalking — 1 in 6.2 Student sexual assault — 1 in 5.7 Domestic violence — 1 in 3.7 Night walk assault — 1 in 3.6 Bicycle theft — 1 in 2.9 Sexual assault — 1 in 2.9 Home burglary — 1 in 2.6 Sexual harassment (lifetime) — 1 in 1.6 Water scarcity — 1 in 2.5 Carrington-class solar storm — 1 in 1.9 WAIS tipping point — 1 in 1.1 Indoor cat escape harm — 1 in 10 Off-leash dog bite — 1 in 8.9 Rabbit dies in 4 years — 1 in 3.3 Dog bite (non-fatal) — 1 in 1.8 Hamster dies before teenager — 1 in 1.0 Vitamin D gap — 1 in 2.9 Undercooked food — 1 in 1.6 Raw meat cross-contamination — 1 in 1.4 Food left out — 1 in 1.2 AI voice scam — 1 in 2.9 Online scam loss — 1 in 2.5 Teen cyberbullying — 1 in 2.0 Kids & explicit content — 1 in 1.9 Data breach — 1 in 1.1 Miscarriage — 1 in 6.7 Teen suicide attempt — 1 in 5.6 Postpartum depression — 1 in 4.8 Painkiller before infant vaccination — 1 in 3.8 Excessive pregnancy weight — 1 in 2.6 Unvaxxed child & measles — 1 in 2.0 Elder fraud loss — 1 in 10 Pension fund collapse — 1 in 10 Personal bankruptcy — 1 in 10 Housing crash — 1 in 8.3 Crypto total loss — 1 in 6.7 IRS audit — 1 in 6.7 Visa overstay deportation — 1 in 5.6 Long term disability working age — 1 in 4.0 Student loan default — 1 in 3.8 Whistleblower retaliation — 1 in 3.2 Career obsolescence — 1 in 2.9 Forced job exit before retirement — 1 in 2.9 Retirement shortfall — 1 in 2.6 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Deportation (undocumented) — 1 in 1.8 Funeral cost shock — 1 in 1.8 Identity theft — 1 in 1.7 Credit card fraud — 1 in 1.5 School bullying — 1 in 1.5 Insurance claim denial — 1 in 1.4 Frontline soldier casualty — 1 in 1.3 Economic recession — 1 in 1.0 Stock market crash — 1 in 1.0 Hail roof damage — 1 in 3.0 Dry toilet paper harm — 1 in 100 Secondhand smoke — 1 in 91 Gaming disorder (adults) — 1 in 83 High-heel ER visit — 1 in 79 Child throwing object — 1 in 67 Medication reaction — 1 in 58 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 Drug overdose — 1 in 42 Benzo dependence — 1 in 40 Tap water lead — 1 in 40 Medication misuse — 1 in 35 Traumatic brain injury — 1 in 33 Hospital infection — 1 in 31 Air pollution — 1 in 29 End-stage kidney disease — 1 in 29 Traveler's diarrhea (water) — 1 in 26 Skiing injury — 1 in 26 Bipolar disorder — 1 in 23 Dental tourism complication — 1 in 20 Pet parasites — 1 in 20 Undiagnosed ADHD — 1 in 20 Adult-onset food allergy — 1 in 19 Indoor cooking smoke — 1 in 18 Non-Alzheimer's dementia — 1 in 17 Working-age disabling stroke — 1 in 17 Cannabis use disorder — 1 in 16 Stroke — 1 in 15 Parent death/disability — 1 in 14 Severe hearing loss — 1 in 14 Type 2 diabetes — 1 in 13 Appendicitis — 1 in 13 Untreated depression — 1 in 13 Untreated back pain disability — 1 in 13 Heart disease — 1 in 12 Medical error death — 1 in 12 Compulsive sexual behavior — 1 in 12 Eating disorder — 1 in 11 Hip replacement — 1 in 11 Kidney stones — 1 in 11 Sedentary lifestyle — 1 in 11 Salon infection — 1 in 11 Ovarian cancer — 1 in 91 Colorectal cancer — 1 in 77 Breast cancer — 1 in 59 Liver cancer — 1 in 59 Lung cancer — 1 in 56 Prostate cancer — 1 in 50 Melanoma (UV) — 1 in 29 Low-fiber CRC risk — 1 in 23 Red meat & CRC — 1 in 21 Charred meat & cancer — 1 in 20 Maintenance crash — 1 in 83 Driving on sedating meds — 1 in 77 Texting + driving — 1 in 56 Driving after cannabis — 1 in 53 Eating while driving — 1 in 53 Unbelted crash death — 1 in 53 Speeding 20% over limit — 1 in 48 Motorcycle no helmet — 1 in 45 Spaceflight (astronaut) — 1 in 42 Video watching + driving — 1 in 32 Drowsy driving — 1 in 26 E-scooter injury — 1 in 26 Cruise ship norovirus — 1 in 24 Driving at 0.10% BAC — 1 in 16 Catalytic converter theft — 1 in 83 Pickpocketed while traveling — 1 in 38 Stabbed in an assault — 1 in 37 Vehicle theft — 1 in 34 Street robbery / mugging — 1 in 26 Wrongful conviction — 1 in 24 Drink spiking — 1 in 17 Protest under autocracy — 1 in 12 AMOC collapse — 1 in 20 Sting anaphylaxis — 1 in 50 Cat collar injury — 1 in 25 Fish bone injury — 1 in 68 Restaurant food poisoning — 1 in 58 Vegetarian deficiency — 1 in 25 Intimate deepfake — 1 in 25 Social media problematic use — 1 in 13 Infant fall — 1 in 100 Childbirth death (SSA) — 1 in 55 Co-sleeping death — 1 in 43 Toddler stair fall — 1 in 37 Play swing & slide injury — 1 in 33 Autism diagnosis — 1 in 31 C-section complications — 1 in 29 Toy injury requiring ER (child) — 1 in 21 Preeclampsia — 1 in 20 Severe birth tearing — 1 in 17 Gestational diabetes — 1 in 13 Child fall head injury — 1 in 12 Sports betting financial ruin — 1 in 100 Fighter pilot death — 1 in 48 Commercial fishing career death — 1 in 45 Logging career death — 1 in 34 Dying without heir — 1 in 33 Medical bankruptcy — 1 in 25 Compulsive buying disorder — 1 in 20 Rental listing scam loss — 1 in 20 Mortgage foreclosure — 1 in 14 Musculoskeletal LTD claim — 1 in 14 Day-trading losses — 1 in 13 Extremist govt catastrophe — 1 in 13 Hurricane home destruction — 1 in 17 LASIK complications — 1 in 1,000 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Sickle cell disease — 1 in 365 Counterfeit medicine — 1 in 361 Spinal cord injury — 1 in 313 Childhood cancer diagnosis — 1 in 285 Next pandemic death — 1 in 208 Dengue (travel) — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Schizophrenia — 1 in 143 Accidental fall — 1 in 135 Parkinson's — 1 in 125 Sudden death during exercise — 1 in 123 Suicide (US) — 1 in 121 Opioid addiction — 1 in 114 Tuberculosis (global) — 1 in 108 Radon cancer — 1 in 435 Testicular cancer — 1 in 250 Cervical cancer — 1 in 167 Pancreatic cancer — 1 in 125 Pedestrian death — 1 in 806 Motorcycle crash — 1 in 694 Boating drowning — 1 in 685 Driver kills pedestrian — 1 in 552 Phone-distracted walking injury — 1 in 400 EV battery fire — 1 in 333 Cyclist killed by car — 1 in 196 Hand-held phone call + driving — 1 in 143 Petrol car fire — 1 in 125 Self-driving car fatality — 1 in 115 Car crash — 1 in 105 Firefighter duty death — 1 in 455 Police duty death — 1 in 313 Homicide — 1 in 287 Pig-butchering scam — 1 in 106 Extreme heat — 1 in 333 Climate change death — 1 in 204 Swallowed bee/wasp — 1 in 500 Bat bite & rabies — 1 in 238 Mosquito-borne disease — 1 in 190 Food poisoning (global) — 1 in 317 Solar panel fire — 1 in 667 Untreated childhood scoliosis — 1 in 1,000 Child window fall — 1 in 855 Walker stair fall — 1 in 625 Baby walker injury — 1 in 455 Maternal mortality — 1 in 272 Untreated childhood flat feet — 1 in 250 Maternal age & birth defects — 1 in 200 Child death (<18) — 1 in 143 Caving career death — 1 in 167 EMS duty death — 1 in 794 Civilian war casualty — 1 in 499 Soldier in combat — 1 in 270 Mining career death — 1 in 214 Gambling financial ruin — 1 in 159 Wildfire home destruction — 1 in 120 Lightning home fire — 1 in 105 Malaria (travel) — 1 in 10,000 Infection from shared drink — 1 in 10,000 Chagas disease — 1 in 8,475 Wild berry fox tapeworm — 1 in 8,475 Schistosomiasis death — 1 in 6,667 Sudden death (young adult) — 1 in 3,922 Unsafe wiring — 1 in 3,390 Sepsis from wound — 1 in 2,857 Anesthesia awareness — 1 in 2,500 Heat stroke (outdoor) — 1 in 1,905 House fire — 1 in 1,818 Rabies from dogs — 1 in 1,449 Drowning — 1 in 1,379 Shallow-water diving SCI — 1 in 1,111 Choking — 1 in 1,099 EVALI vaping hospitalization — 1 in 1,064 Betel nut cancer — 1 in 1,290 Blood clot (flight) — 1 in 4,651 Killing a cyclist — 1 in 3,937 Teen road-crash death — 1 in 3,030 Child rear bike seat — 1 in 2,500 Child without restraint — 1 in 2,000 Fatal police encounter — 1 in 4,739 Honor killing — 1 in 2,381 Intimate-partner homicide — 1 in 1,767 Hurricane — 1 in 8,929 Drought famine death — 1 in 6,536 Blizzard death — 1 in 4,367 Earthquake — 1 in 3,802 Dog chocolate death — 1 in 2,000 Food poisoning (US) — 1 in 1,862 Fish mercury — 1 in 1,695 Phone/laptop battery fire — 1 in 1,136 SIDS — 1 in 7,143 Laundry pod ingestion — 1 in 6,494 Untreated infant hip dysplasia — 1 in 5,000 Pool drowning — 1 in 2,299 War (civilian) — 1 in 2,000 Fatal bee/wasp sting — 1 in 76,923 Anesthesia death — 1 in 50,000 Dog hot car death — 1 in 41,667 Anaphylaxis — 1 in 27,548 Chiropractic neck manipulation — 1 in 16,667 CO poisoning — 1 in 14,006 Hepatitis A (travel) — 1 in 12,500 Skipping allergy immunotherapy — 1 in 11,111 Acrylamide & cancer — 1 in 16,667 Bus crash — 1 in 100,000 Plane crash — 1 in 58,824 Child pedestrian (residential) — 1 in 45,455 Railroad crossing death — 1 in 20,704 Child bike trailer — 1 in 14,286 Acid attack — 1 in 89,286 Terrorism — 1 in 77,519 Child stranger abduction — 1 in 38,760 Stranger kidnapping — 1 in 35,211 Dowry death — 1 in 13,158 Accidental gun death — 1 in 11,299 Wildfire — 1 in 100,000 Tornado — 1 in 80,645 Tsunami — 1 in 52,632 Ocean drowning — 1 in 29,155 Flood — 1 in 20,202 Landslide death — 1 in 18,416 Supervolcano eruption — 1 in 12,376 Crocodile attack — 1 in 84,746 Bee sting — 1 in 78,927 Fatal scorpion sting — 1 in 26,110 Plastic container leaching — 1 in 16,949 Infant in car seat — 1 in 64,935 Bouncer chair fall — 1 in 60,606 Toddler choking — 1 in 50,000 Unsupervised infant choking — 1 in 50,000 Magnet ingestion — 1 in 12,048 Snorkeling death — 1 in 21,739 Pet in transport — 1 in 20,000 Landmine or UXO injury — 1 in 14,728 Vaccine reaction — 1 in 763,359 Aluminum & Alzheimer's — 1 in 169,492 Residential gas leak — 1 in 140,845 Child hot car death — 1 in 102,041 Glyphosate & cancer — 1 in 1,000,000 Teflon cookware cancer — 1 in 169,492 Roller coaster injury — 1 in 312,500 Cruise ship accident — 1 in 188,679 Ferry sinking — 1 in 133,333 Turbulence injury — 1 in 114,943 School shooting — 1 in 192,308 Mass shooting — 1 in 113,636 Nuclear accident — 1 in 833,333 Avalanche — 1 in 210,526 Lightning — 1 in 209,205 Snake bite — 1 in 884,956 Spider bite — 1 in 833,333 Hippo attack — 1 in 564,972 Dog bite — 1 in 142,045 Pesticide residue — 1 in 1,000,000 Dirty can illness — 1 in 200,000 PLA bioplastic harm — 1 in 169,492 Charger left plugged in — 1 in 200,000 Infant swing death — 1 in 714,286 Child blind cord strangulation — 1 in 416,667 Child plastic bag suffocation — 1 in 263,158 Button battery — 1 in 250,000 Inclined sleeper death — 1 in 238,095 Elevator/escalator death — 1 in 188,324 Japanese encephalitis (travel) — 1 in 2,000,000 Kid + front airbag — 1 in 10,000,000 Asteroid impact — 1 in 1,351,351 Banana spider eggs — 1 in 10,000,000 Shark attack — 1 in 5,681,818 Bear attack — 1 in 3,787,879 Wild berry poisoning — 1 in 2,222,222 Space debris hits property — 1 in 10,000,000 Piranha attack — 1 in 135,135,135 Phone at gas pump — 1 in 1,000,000,000 Phone on plane — 1 in 1,000,000,000 Alien contact — 1 in 169,491,525
Lottery jackpot 1 in 95,238